Risk Assessment and Management for Ships and Offshore Structures helps engineers accurately analyze results and apply engineering principles to a vast range of oil and gas structures. Bridging theoretical-depth and practical application, this reference gives specific applications for risk assessment and integrity management for different ships and offshore structures, covering aspects of offshore production and drilling systems from the sea floor to the surface. Divided into different sections, and starting with a discussion of risk management background, the book then covers risk assessment for specific installations such as BOPs, marine production systems, subsea systems, deepwater production risers and pipelines.
This book provides offshore petroleum engineers with both the theoretical principles and practical application skills needed to face todays offshore challenges and structures.
- Delivers wide coverage on risk assessment and asset management for todays oil and gas offshore structures
- Provides engineers with real statistical data collections and analysis from historical data to calculate failure frequency, a key task in risk management
- Bridges theoretical principles and practical applications, including upcoming challenges and technological advances
PART 1 RISK MANAGEMENT
1. Risk Management
2. Risk Assessment Methodology
3. Failure Frequency
4. Failure Consequence5. Human Factors
6. Databases for Failure Frequency
7. Computer Software for Risk Assessment
PART 2 RISK ASSESSMENT FOR SPECIFIC INSTALLATIONS
8. Risk Assessment for BOP and Drilling Risers
9. Risk Assessment for Marine Production Systems
10. Risk Assessment for Deepwater Production and Offloading Risers
11. Risk Assessment for Subsea Systems
12. Risk Assessment for Pipelines
PART 3 OIL SPILL RISK ASSESSMENT FOR SPECIFIC INSTALLATIONS
13. Oil Spill Risk Assessment for BOP and Drilling Risers
14. Oil Spill Risk Assessment for Marine Production Systems
15. Oil Spill Risk Assessment for Deepwater Production and Offloading Risers
16. Oil Spill Risk Assessment for Subsea Systems
17. Oil Spill Risk Assessment for Pipelines
PART 4 RISK MANAGEMENT FOR FIRES AND EXPLOSIONS
18. Hydrocarbon Leaks from Process Systems
19. Fire Loads
20. Structural Response Due to Fires
21. Design against Fire Accidents
22. Explosion Loads
23. Structural Response Due to Explosions
24. Design against Explosion Accidents
PART 5 RISK MANAGEMENT FOR COLLISION AND GROUNDING
25. Ship/Floater Collisions
26. Ship Collision with Fixed Platforms
27. Ship Grounding
PART 6 ASSET INTEGRITY MANAGEMENT
28. Asset Integrity Management (AIM) in Offshore Installation
29. Risk Based Inspection (RBI) for Offshore Pipelines
30. Risk Based Inspection (RBI) for Offshore Structures
31. Safety Integrity Level (SIL) in Offshore Installation
32. Reliability Centered Maintenance (RCM) in Offshore Installation
Dr. Yong Bai holds the position of Chair Professor at Zhejiang University (China) and is also an academician at the Norwegian Academy of Technical Sciences. He is a fellow of the US Society of Naval Architects and Marine Engineers and the UK Royal Institution of Naval Architects. With an extensive background in offshore engineering structures and pipelines, Prof. Bai has held professorships at renowned universities, significantly contributing to the global offshore oil and gas industry through his publications and innovative achievements. Dr. Jeom Kee Paik, Professor of Marine Technology, the University College London (UK), is a National Special-Talent and chair professor at Ningbo University and Harbin Engineering University (China). An international fellow of the UK Royal Academy of Engineering and a fellow of various prestigious institutions, Prof. Paiks research interests include nonlinear structural mechanics, advanced structural safety studies, limitstate-based design, and quantitative risk assessment and management. He is recognized for pioneering a proactive approach of digital healthcare engineering for aging ships, offshore structures, and seafarers working under hostile ocean environments or remote areas, using digital and communication technologies, AI, and machine learning.
